Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 조인휘 | - |
dc.date.accessioned | 2018-09-28T04:46:08Z | - |
dc.date.available | 2018-09-28T04:46:08Z | - |
dc.date.issued | 2016-08 | - |
dc.identifier.citation | IET COMMUNICATIONS, v. 10, NO. 12, Page. 1508-1521 | en_US |
dc.identifier.issn | 1751-8628 | - |
dc.identifier.issn | 1751-8636 | - |
dc.identifier.uri | https://www.crossref.org/iPage?doi=10.1049%2Fiet-com.2015.0223 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/76245 | - |
dc.description.abstract | The solar powered energy harvesting sensor node is a key technology for Internet of Things (IoT), but currently it offers only a small amount of energy storage and is capable of harvesting only a trivial amount of energy. Therefore, new technology for managing the energy associated with this sensor node is required. In particular, it is important to manage the transmission interval because the level of energy consumption during data transmission is the highest in the sensor node. If the proper transmission interval is calculated, the sensor node can be used semi-permanently. In this study, the authors propose an energy prediction algorithm that uses the light intensity of fluorescent lamps in an indoor environment. The proposed algorithm can be used to accurately estimate the amount of energy that will be harvested by a solar panel using a weighted average for light intensity. Then, the optimal transmission interval is calculated using the amount of predicted harvested energy and residual energy. The results from the authors’ experimental testbeds show that their algorithm's performance is better than the existing approaches. The energy prediction error of their algorithm is approximately 0.5%. | en_US |
dc.language.iso | en | en_US |
dc.publisher | INST ENGINEERING TECHNOLOGY-IET | en_US |
dc.subject | energy harvesting | en_US |
dc.subject | Internet of Things | en_US |
dc.subject | solar cell arrays | en_US |
dc.subject | telecommunication power management | en_US |
dc.subject | wireless sensor networks | en_US |
dc.subject | energy management algorithm | en_US |
dc.subject | solar-powered energy harvesting wireless sensor node | en_US |
dc.subject | IoT | en_US |
dc.subject | energy storage | en_US |
dc.subject | transmission interval management | en_US |
dc.subject | energy consumption level | en_US |
dc.subject | energy prediction algorithm | en_US |
dc.subject | fluorescent lamp light intensity | en_US |
dc.subject | solar panel | en_US |
dc.subject | optimal transmission interval | en_US |
dc.subject | residual energy | en_US |
dc.subject | energy prediction error | en_US |
dc.title | Energy Management Algorithm for Solar-powered Energy Harvesting Wireless Sensor Node for IoT | en_US |
dc.type | Article | en_US |
dc.relation.no | 12 | - |
dc.relation.volume | 10 | - |
dc.identifier.doi | 10.1049/iet-com.2015.0223 | - |
dc.relation.page | 1508-1521 | - |
dc.relation.journal | IET COMMUNICATIONS | - |
dc.contributor.googleauthor | Shin, Minchul | - |
dc.contributor.googleauthor | Joe, Inwhee | - |
dc.relation.code | 2016003502 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF COMPUTER SCIENCE | - |
dc.identifier.pid | iwjoe | - |
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